An interim determination of health gain from oral cancer and precancer screening: 2. Developing a model of population screening.
OBJECTIVE
To design a simulation model of population screening for oral cancer and precancer and to obtain estimates of quality adjusted life years (QALYs) and lives gained from screening, using decision analysis.


METHODS
A hypothetical opportunistic screening programme was compared with the status quo (no screening). Variables included in the model were attendance (50 per cent of the eligible population); prevalence of oral cancer (0.098 per cent) and precancer (2.57 per cent), positive (0.67) and negative (0.99) predictive values of screening, stage distribution of cancer (40 per cent stage 1, 60 per cent stage 2+ without screening; 60 per cent stage 1, 40 per cent stage 2+ with screening); average survival (precancer, 19.2 years; stage 1, 14.6 years; stage 2+, 10.8 years); and the public's perceived utilities of the various outcomes (health, 1.00; precancer, 0.92; stage 1 cancer, 0.88; stage 2+ cancer, 0.68). One cycle of the programme was modelled.


METHODS
Screening would be carried out in dental practices.


METHODS
A notional population of 100,000 adults of average age 55 years and 20 years life expectancy entered each decision pathway (screening or status quo).


METHODS
Systematic clinical examination of the oral soft tissues.


METHODS
QALYs and equivalent lives saved.


RESULTS
Assuming 50 per cent attended, the population offered screening achieved 1,993,094 QALYs. With no screening the corresponding end point was 1,992,982 QALYs. The gain from screening was therefore 56 QALYs representing an equivalent of 2.8 lives saved.


CONCLUSIONS
Though a simplification, this model is likely to be more reliable than intuitive prediction and is amenable to sensitivity analysis of different screening strategies. A modest health gain from screening was predicted by the model.
Downer
M C
MC
Eastman Dental Institute, London, UK.
Jullien
J A
JA
Speight
P M
PM
D000328:Adult; D003198:Computer Simulation; D003661:Decision Support Techniques; D003729:Dental Care; D005544:Forecasting; D006801:Humans; D008017:Life Expectancy; D008403:Mass Screening; D008875:Middle Aged; D009062:Mouth Neoplasms / Q000473:pathology / Q000517:prevention & control*; D009367:Neoplasm Staging; D017063:Outcome Assessment, Health Care; D010342:Patient Acceptance of Health Care; D011159:Population Surveillance; D011230:Precancerous Conditions / Q000473:pathology / Q000517:prevention & control*; D011237:Predictive Value of Tests; D015995:Prevalence; D011639:Public Opinion; D019057:Quality-Adjusted Life Years; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D015996:Survival Rate